title: Automatic detection of diabetic retinopathy exudates from non-dilated retinal images using mathematical morphology methods.
abstract: Diabetic retinopathy is a complication of diabetes that is caused by changes in the blood vessels of the retina. The symptoms can blur or distort the patient's vision and are a main cause of blindness. Exudates are one of the primary signs of diabetic retinopathy. Detection of exudates by ophthalmologists normally requires pupil dilation using a chemical solution which takes time and affects patients. This paper investigates and proposes a set of optimally adjusted morphological operators to be used for exudate detection on diabetic retinopathy patients' non-dilated pupil and low-contrast images. These automatically detected exudates are validated by comparing with expert ophthalmologists' hand-drawn ground-truths. The results are successful and the sensitivity and specificity for our exudate detection is 80% and 99.5%, respectively.
authors.affiliation: Department of Information Technology, Sirindhorn International Institute of Technology (SIIT), Thammasat University, Muang, Pathumthani 12000, Thailand. akara@siit.tu.ac.th
authors.forename: Akara
authors.initials: A
authors.lastname: Sopharak
authors.forename: Bunyarit
authors.initials: B
authors.lastname: Uyyanonvara
authors.forename: Sarah
authors.initials: S
authors.lastname: Barman
authors.forename: Thomas H
authors.initials: TH
authors.lastname: Williamson
mesh_terms: D003930:Diabetic Retinopathy / Q000175:diagnosis* / Q000473:pathology; D005122:Exudates and Transudates; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008953:Models, Anatomic; D010363:Pattern Recognition, Automated / Q000379:methods; D010784:Photomicrography / Q000379:methods*; D012016:Reference Values; D012160:Retina / Q000473:pathology; D012171:Retinal Vessels / Q000473:pathology; D012680:Sensitivity and Specificity; D014941:Work Simplification